Violence in harm reduction: Exploring the social, political, and emotional conditions of harm reduction work
Bibliographic record
Abstract
Harm reduction professionals strive to reduce the health, social, and legal consequences associated with drug use in contexts permeated by violence. Building on fieldwork in Paris and Barcelona, we examine how they make sense of this violence. In Paris, the discussion of violence primarily hinges on the narratives of suffering from people who use drugs and the obstacles posed by the political context. In Barcelona, the narrative emphasizes precariousness and deficiencies in organizational violence management, which intensifies perceptions of violence. Moving beyond polarized understandings of violence, we argue that violence is socially constructed as an inherent aspect of the culture of harm reduction work. This process involves mechanisms of naturalization, delegitimization, and normalization, shaping work experiences and the construction of the professional self. Although violence manifests in similar forms and manifestations across settings, experiences of that violence differ based on how it perpetuates power dynamics and inequalities within the workplace.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".